Critical seed transfer distances for selected tree species in eastern North America
Bibliographic record
Abstract
Forest planting events present key opportunities to enhance forest adaptation and growth through the selection of appropriate growing materials (seeds and seedlings). Critical to such efforts is knowledge of the climatic distance that seed sources can be moved before significant growth forfeitures are incurred. These limits, referred to here as critical seed transfer distances (CSTD), can be used to identify a potential seed procurement region for any given planting site and can readily incorporate climate change projections. We assembled provenance trial data from a variety of sources and employed transfer functions to derive CSTDs for five major tree species in eastern North America. Calculated transfer limits were large, indicating that seed sources could be moved significant climatic distances before height growth was less than 90 percent relative to that of the local seed source. These broad relationships would allow considerable flexibility in resulting seed transfer systems; however, given the significant uncertainty surrounding climate change – particularly in the location and timing of extreme weather events – prudent application of seed transfer limits may be appropriate. Synthesis: We assembled and analyzed a significant amount of provenance data to derive novel information on seed movement limits for five tree species in eastern North America. This information will support forest managers in ongoing efforts to incorporate climate change into forest regeneration operations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".